Deciphering the Liquidity and Credit Crunch 2007-2008

Questions & answers

Q1. What two pre-crisis trends in the banking industry does the paper identify as laying the groundwork for the crisis?

The paper identifies, first, banks’ shift from holding loans to an “originate and distribute” model in which loans are pooled, tranched into securities such as collateralized debt obligations, and sold on to investors with varying risk appetites, and second, a shortening of banks’ funding maturity structure – increasing reliance on asset-backed commercial paper (average maturity about 90 days) and overnight repurchase agreements to finance assets with maturities of years or decades, creating a maturity mismatch “transferred to a ‘shadow’ banking system” (pp. 3-5). It notes that the fraction of investment-bank assets financed by overnight repos “roughly doubled from 2000 to 2007,” and that sponsoring banks granted “liquidity backstops” to their off-balance-sheet vehicles, so that “the banking system still bears the liquidity risk from holding long-term assets and making short-term loans even though it does not appear on the banks’ balance sheets” (p. 4).

Q2. How does the paper define and distinguish “funding liquidity” and “market liquidity,” and why does this distinction matter?

Funding liquidity is defined as “the ease with which expert investors and arbitrageurs can obtain funding from (possibly less informed) financiers,” while market liquidity is “low when it is difficult to raise money by selling the asset (instead of by borrowing against it)”; the paper states that “the mechanisms that explain why liquidity can suddenly evaporate operate through the interaction of market liquidity and funding liquidity” (pp. 20-22, citing Brunnermeier and Pedersen 2009). Funding liquidity risk is broken into three forms – margin/haircut risk, rollover risk, and redemption risk – each of which the paper states is “only detrimental when the assets can be sold only at fire-sale prices – that is, when market liquidity is low” (p. 21).

Q3. How does the “loss spiral” work, and what makes it self-reinforcing?

Using a worked numerical example, the paper shows that a leveraged investor who buys $100 million of assets on 10 percent margin ($10 million own capital, $90 million borrowed, leverage ratio 10) who then suffers a $5 million paper loss has only $5 million of capital left; holding the leverage ratio constant forces the investor to sell $45 million of assets exactly when prices are already low, and “these sales depress the price further, inducing more selling and so on” (pp. 22-23). The paper attributes the equilibrium persistence of this spiral partly to other potential buyers facing similar constraints at the same time (citing Shleifer and Vishny 1992) and partly to buyers finding it profitable to wait the spiral out, or in extreme cases to engage in “predatory trading” that deliberately forces others to liquidate at fire-sale prices.

Q4. What is the “margin/haircut spiral,” and why do margins rise (rather than fall) exactly when prices are already depressed?

The margin spiral reinforces the loss spiral: as margins or haircuts rise, “the investor has to sell even more because the investor needs to reduce its leverage ratio,” and the paper reports that Brunnermeier and Pedersen (2009) show this can generate “a vicious cycle… leading to the possibility of multiple equilibria,” with Adrian and Shin (2009) confirming the pattern empirically for investment banks (pp. 23-24). The paper gives three reasons margins counterintuitively rise after a price drop rather than fall to reflect a buying opportunity: unexpected price shocks can signal higher future volatility; asymmetric-information concerns make financiers wary of being handed the “lemons” among posted collateral; and lenders who naively extrapolate volatility from recent data mechanically raise margins after large moves (p. 23).

Q5. How can a “lending channel” dry up even when borrowers’ own creditworthiness has not changed?

The paper distinguishes two mechanisms by which lenders with limited capital of their own restrict lending independent of borrower quality: moral hazard in monitoring, which arises when a fall in intermediaries’ own net worth reduces their incentive to monitor borrowers carefully (citing Holmström and Tirole 1997, 1998), and precautionary hoarding, in which lenders anticipate needing funds for their own future shocks and projects (pp. 25-26). The paper calls the troubles in the 2007-08 interbank lending market “a textbook example of precautionary hoarding by individual banks,” driven by banks’ uncertainty about whether conduits and off-balance-sheet vehicles would draw on their sponsored credit lines, and about whether other banks were similarly exposed – effects that drove the spike in LIBOR relative to Treasury bill rates (p. 26).

Q6. In what sense can institutions other than deposit-taking banks experience a classic “run,” and which 2008 cases illustrate this?

The paper extends the logic of bank runs – a first-mover advantage because early withdrawers are paid in full while late withdrawers bear the cost of either insufficient asset value or fire-sale liquidation of long-maturity assets – to any financial institution funded by short-term, redeemable claims, including commercial paper issuers, prime-brokerage clients, and hedge-fund or mutual-fund investors; it states that “Bear Stearns essentially experienced a bank run in March 2008 when hedge funds… pulled out those funds,” and that “in September 2008, AIG faced a ‘margin run’” as counterparties demanded additional collateral on its credit default swap positions (pp. 26-27). A worked example shows how a fund holding $50 million cash and $50 million of assets that can only be sold for $30 million under pressure pays early withdrawers in full but leaves late withdrawers a smaller share once illiquid assets must be sold, generating the same first-mover incentive to preempt (p. 27).

Q7. What is “network risk,” and how did it manifest in the Bear Stearns and Lehman episodes?

The paper shows, via a stylized interest-rate-swap example among Goldman Sachs, Bear Stearns, a hedge fund, and a private equity fund, that even when all parties’ exposures would fully net out in a multilateral agreement, fear of counterparty credit risk can prevent that netting from happening because “each party only knows its own contractual obligations,” forcing all sides to post additional liquidity or buy costly credit protection against one another (pp. 27-28). It reports that this is exactly what happened “in the week after Lehman’s bankruptcy, September 15-19, 2008,” when major investment banks, worried about each other’s solvency, all bought CDS protection against one another and “the already high prices on credit default swaps of the major investment banks almost doubled,” with AIG’s CDS price “more than doubled within two trading days” (p. 28). The paper also recounts how a brief, misread delay in Goldman’s renewal of a swap contract with Bear Stearns on March 11-12, 2008 was “leaked to the media and might have contributed to the run on Bear Stearns” (p. 27).

Q8. What does the paper conclude about why this crisis resembled, yet differed from, a classical banking crisis, and what does it imply for financial regulation?

The conclusion states that “while each crisis has its own specificities, the current one has been surprisingly close to a ‘classical banking crisis’… What is new about this crisis is the extent of securitization, which led to an opaque web of interconnected obligations” (p. 29). The paper argues the amplification mechanisms it identifies show that “fire-sale externalities and network effects suggest that financial institutions have an individual incentive to take on too much leverage, to have excessive mismatch in asset-liability maturities, and to be too interconnected,” framing these as starting points for redesigning financial regulation and risk measurement (citing the author’s own CoVaR measure, developed with Adrian, as one such tool) (p. 29).